Traditional range-dependency compensation space time adaptive processing(STAP)methods usually involve aligning the clutter spectrums in a certain point to reduce the clutter non-homogeneity.A novel compensation STAP m...Traditional range-dependency compensation space time adaptive processing(STAP)methods usually involve aligning the clutter spectrums in a certain point to reduce the clutter non-homogeneity.A novel compensation STAP method is proposed as an improved Doppler warping(DW)method for airborne radar with non-sidelooking radar.This method facilitates DW method to bring clutter spectrum of different range gates together in the mainlobe and subsequently compensation to accomplish space angle of different range gates alignment at multiple Doppler bins.Simulation results show that the proposed method can further reduce the clutter non-homogeneity of non-sidelooking array and significantly outperform traditional algorithms with only a little increase of the computation load.展开更多
传统多普勒频移(DW)法对天空双基地预警雷达(Space-Air Based Bistatic Radar,SABBR)非平稳杂波具有较好的抑制效果,但如果雷达几何配置关系未知,杂波方位-多普勒曲线无法得到,传统DW法无法使用。针对这一问题,提出一种基于DW法的改进算...传统多普勒频移(DW)法对天空双基地预警雷达(Space-Air Based Bistatic Radar,SABBR)非平稳杂波具有较好的抑制效果,但如果雷达几何配置关系未知,杂波方位-多普勒曲线无法得到,传统DW法无法使用。针对这一问题,提出一种基于DW法的改进算法,首先在慢时间维对杂波数据进行分块处理,减少非平稳性的影响;然后采用最小二乘估计待检测单元杂波方位-多普勒曲线,将参考单元的时域导向矢量与待检测单元对齐,估计出待检测单元的杂波协方差矩阵;最后进行STAP处理。仿真结果表明,该方法能够改善杂波抑制性能,且适用性更强。展开更多
将动态时间规整(Dynamic Time Warping)算法应用于地面车辆目标的分类识别中。基于微多普勒效应原理,建立了轮式车辆和履带式车辆雷达回波模型,对两种车辆目标微多普勒信号的差异性进行了分析,并结合实测数据,验证了理论分析的正确性。...将动态时间规整(Dynamic Time Warping)算法应用于地面车辆目标的分类识别中。基于微多普勒效应原理,建立了轮式车辆和履带式车辆雷达回波模型,对两种车辆目标微多普勒信号的差异性进行了分析,并结合实测数据,验证了理论分析的正确性。在杂波抑制及速度归一化处理的基础上,利用动态时间规整算法,将提取出的车辆目标的累积失真距离作为目标分类识别的依据,实现了轮式车辆和履带式车辆的自动分类。基于实测数据的实验结果表明,该方法在不同信噪比条件下都具有较好的分类性能。展开更多
基金Supported by the National Natural Science Foundation of China(61201459,61071165)the National Defense Basic Science Research Scheme(B2520110008)the Program for New Century Excellent Talents in University(NCET-09-0069)
文摘Traditional range-dependency compensation space time adaptive processing(STAP)methods usually involve aligning the clutter spectrums in a certain point to reduce the clutter non-homogeneity.A novel compensation STAP method is proposed as an improved Doppler warping(DW)method for airborne radar with non-sidelooking radar.This method facilitates DW method to bring clutter spectrum of different range gates together in the mainlobe and subsequently compensation to accomplish space angle of different range gates alignment at multiple Doppler bins.Simulation results show that the proposed method can further reduce the clutter non-homogeneity of non-sidelooking array and significantly outperform traditional algorithms with only a little increase of the computation load.
文摘传统多普勒频移(DW)法对天空双基地预警雷达(Space-Air Based Bistatic Radar,SABBR)非平稳杂波具有较好的抑制效果,但如果雷达几何配置关系未知,杂波方位-多普勒曲线无法得到,传统DW法无法使用。针对这一问题,提出一种基于DW法的改进算法,首先在慢时间维对杂波数据进行分块处理,减少非平稳性的影响;然后采用最小二乘估计待检测单元杂波方位-多普勒曲线,将参考单元的时域导向矢量与待检测单元对齐,估计出待检测单元的杂波协方差矩阵;最后进行STAP处理。仿真结果表明,该方法能够改善杂波抑制性能,且适用性更强。
文摘将动态时间规整(Dynamic Time Warping)算法应用于地面车辆目标的分类识别中。基于微多普勒效应原理,建立了轮式车辆和履带式车辆雷达回波模型,对两种车辆目标微多普勒信号的差异性进行了分析,并结合实测数据,验证了理论分析的正确性。在杂波抑制及速度归一化处理的基础上,利用动态时间规整算法,将提取出的车辆目标的累积失真距离作为目标分类识别的依据,实现了轮式车辆和履带式车辆的自动分类。基于实测数据的实验结果表明,该方法在不同信噪比条件下都具有较好的分类性能。
